Experiments on bridging across languages and genres Yulia Grishina - - PowerPoint PPT Presentation

Experiments on bridging across languages and genres

Yulia Grishina

Applied Computational Linguistics University of Potsdam / Germany

Goals

• introduce a typology for bridging relations
• use an existing one for near-identity & apply it to

German

• validate on a corpus of different languages and

genres

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Experiments?

• Design for German - Apply on German - Transfer to

English and Russian

• manual transfer
• aiming at automatic projection via parallel corpora

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Annotation projection

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Coreference chains; automatic; F1 DE = 50.8 F1 RU = 67.2

EN RU DE

Bridging & near-identity

• Bridging: indirect relations that can only be

inferred based on the common knowledge shared by the speaker and the listener (e.g. part-whole, set-membership)

• Near-identity: two NPs are almost identical, but

differ in one crucial dimension (e.g. time)

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Bridging: 2 viewpoints

➡ Information Status ➡ an IS subcategory, along with given, new, etc.

(Gardent et al., 2003), (Nissim et al, 2004), (Ritz et al., 2008), (Riester et al., 2010), (Markert et al., 2012)

➡ Coreference ➡ a separate coreference relation, e.g. part-whole, set-

membership (Poesio et al., 2004), (Poesio and Artstein, 2008), (Nedoluzhko et al., 2009)

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Annotation

• common coreference annotation guidelines (based on PoCoS

(Krasavina & Chiarcos, 2007), OntoNotes (Hovy et al., 2006))

• uniform annotations in 3 languages
• NP coreference: full NPs, proper names, pronouns
• already annotated with identity coreference
• annotation tool: MMAX-2 (Müller & Strube, 2006),

subsequently converted into CoNLL-2012 format

Parallel corpus

#EN #DE #RU Documents 14 14 10 Sentences 589 598 431 Tokens 11908 11894 8106 REs 1350 1395 1085 Coreference chains 259 273 188 Bridging markables 188 432 188 (Grishina and Stede, 2015)

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Parallel corpus

Newswire Narratives Medicine Total EN DE RU EN DE RU EN DE EN DE RU Tokens 5903 6268 5763 2619 2642 2343 3386 3002 11908 11912 8106 Sentences 239 252 239 190 186 192 160 160 589 598 431 REs 558 589 606 470 497 479 322 309 1350 1395 1085 Chains 124 140 140 45 45 48 90 88 259 273 188

• Av. chain

length 4.5 4.2 4.3 10.4 11.04 10.0 3.6 3.5 5.2 5.1 12.3

Annotation

• bridging (Clark, 1975) and near-identity (Recasens

et al., 2010)

• German side of the corpus
• 2 annotators (half of the corpus)
• bridging: examine all definite NPs that are not

linked to anything

• near-identity: check all NPs

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Example annotation

[Daisy Hamilton] was a private detective. [She] was thirty years old and [she] has been a detective for the past two years. Every morning [Daisy] went to [[her]

• ffice]_B1 to wait for phone calls or open [[the

door]_B1] to clients needing [her] services. One day somebody knocked on [the door].

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Annotation: bridging

• PART-WHOLE
• the telephone - the receiver
• SET-MEMBERSHIP
• the European Union - the least developed countries
• ENTITY-ATTRIBUTE/FUNCTION
• Kosovo - the current policy of rejection
• EVENT-ATTRIBUTE
• the regional conflict - the trained fighters
• LOCATION-ATTRIBUTE
• Germany - in the south

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Annotation: bridging

• Annotation principles

➡ semantic relatedness ➡ proximity ➡ identity < near-identity < bridging

[The telephone] rang. I went into [the office] and picked up [the receiver].

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Annotation: bridging

• Annotation principles

➡ semantic relatedness ➡ proximity ➡ identity < near-identity < bridging

[The telephone] rang. I went into [the office] and picked up [the receiver].

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Annotation: bridging

• Annotation principles

➡ semantic relatedness ➡ proximity ➡ identity < near-identity < bridging

[The telephone] rang. I went into [the office] and picked up [the receiver].

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Results: bridging

Poesio (2004) Nedoluzhko et al. (2009) This work Anaphor selection (F-1) 0.22 0.5 0.64 Antecedent selection (F-1) N/A N/A 0.79 Relation assignment (Cohen’s kappa) N/A 0.9 0.98

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Annotation: Near-Identity

• NAME METONYMY
• the US (geographical entity) - the US (the government)
• MERONYMY
• the president - the US (=the president)
• SPATIO-TEMPORAL FUNCTION
• Budapest - the medieval Budapest

(from Recasens et al., 2010)

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Results: near-identity

• small amount of near-identity links in the corpus,

insufficient to compute the IAA

• for German, it conforms to the results of (Recasens

et al., 2012)

• -> it is difficult to annotate near-identity explicitly

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Results: near-identity

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Relation News Narrative Medicine Metonymy 15.79 100.0 0.0 Meronymy 76.32 0.0 28.57 Spatio-temporal function 7.89 0.0 71.43 Other 0.0 0.0 0.0

Distribution of bridging relations (DE)

Location-Attr 14% Event-Attr 7% Entity-Attr/F 62% Set-Membership 4% Part-Whole 13%

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Distribution of bridging across genres (DE)

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News 15% 12% 59% 4% 10% Narratives 63% 37%

Part-Whole Set-Membership Entity-Attr/F Event-Attr Location-Attr

Medicine 1% 72% 10% 17%

Coreference & bridging

• 17% bridging markables that start a coreference

chain

• -> bridging entities are not as important on their
• wn in the text
• 56% coreference chains that have bridging

markables connected to them

• -> bridging markables are important for

coreference entities

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Coreference & bridging

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Length of identity chains and number of their bridging markables Number of bridging markables

4 8 12 16

Coreference chain length

7.5 15 22.5 30 23

Bridging distance

• anaphora+cataphora: 20.55 tokens (av. sentence

length = 24.87 tokens)

• cataphora: -3.6 tokens
• anaphora: 30.96 tokens
• distance does not correlate with prominence

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Transfer

• looking at German, we annotated English and

Russian

• 44% of the German markables transferred
• -> newswire was the most problematic genre

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Transfer

• [Die Terroranschläge in Mumbai im letzten Monat]

sollten nicht nur die Wirtschaft und das Sicherheitsgefühl Indiens treffen. <…> [Die Täter] haben weder ihre Gesichter verhüllt noch sich selbst in der Manier von Selbstmordattentätern in die Luft gesprengt.

• [Last month's terrorist assault in Mumbai] targeted

not only India's economy and sense of security. <…> [The attackers] did not hide their faces or blow themselves up with suicide jackets.

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Transfer

• [Die Terroranschläge in Mumbai im letzten Monat]

sollten nicht nur die Wirtschaft und das Sicherheitsgefühl Indiens treffen. <…> [Die Täter] haben weder ihre Gesichter verhüllt noch sich selbst in der Manier von Selbstmordattentätern in die Luft gesprengt.

• [Last month's terrorist assault in Mumbai] targeted

not only India's economy and sense of security. <…> [The attackers] did not hide their faces or blow themselves up with suicide jackets.

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Russian?

• Strategy: Genitive test

Daisy was in [the office] when someone knocked on [the door]. ✓ [the door] == [the door of the office]

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Distribution of relations across languages

Part-Whole Set-Membership Entity-Attr/F Event-Attr Location-Attr 20 40 60 80

DE EN RU

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Outcomes

• a typology of bridging relations
• annotation of bridging with high inter-annotator

reliability in 3 languages and 3 text domains

• near-identity: application to German
• strong correlation between bridging and

coreference

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Thank you!

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